LLM API cost calculator

Input tokens times the model's input rate, plus output tokens times its output rate, both per 1M tokens. The rate is the cheapest provider listing the model, with input and output taken from that one provider. Cached-input discounts, batch pricing, long-context surcharges and reasoning-token billing are not modelled, because the rates we track do not include them; a workload that uses them will cost less, or more, than the figure here.

About 751,880 English words, or roughly 2,506 book pages at 300 words a page. This page converts at 1.33 tokens per word, OpenAI's rule of thumb that a token is about three quarters of a word; Gemini quotes 60 to 80 words per 100 tokens. Claude 4.7 and later tokenize about 30% denser than earlier Claude models, and text in languages other than English can take 1.5x to 3x the tokens, so treat the conversion as an estimate and count with the provider's tokenizer before relying on it.

About 80K tokens: 200 pages at 300 words is 60,000 words, times 1.33 tokens a word. A 300-page book is about 120K tokens and a typical page about 399. Dense technical text, tables and code run higher.

Per 1M input tokens, the models on this page run from $0.020 (Llama 3.1 8B) to $150.00 (o1-pro); the median is $0.44. Output tokens cost more, typically 3x to 8x the input rate, so a job that writes as much as it reads costs several times a job that only reads.

The cheapest one listing it. Open-weight models are served by several providers at different rates, sometimes severalfold apart; closed models resold through partners are usually at the creator's list price. Every model name links to its page, which lists every provider we track for it.

Rates were last updated on September 15, 2026 and are reviewed against each provider's published pricing page by hand. The full table, with every provider, is on the LLM API pricing page.